A novel control paradigm for large-scale hybrid networks

Informazioni relative al progetto

CLariNet

ID dell’accordo di sovvenzione: 101018826

DOI

10.3030/101018826

Data della firma CE 5 Maggio 2021

Data di avvio 1 Ottobre 2021

Data di completamento 30 Settembre 2026

Finanziato da

• EXCELLENT SCIENCE - European Research Council (ERC)

Costo totale

€ 2 500 000,00

Contributo UE

€ 2 500 000,00

Coordinato da

TECHNISCHE UNIVERSITEIT DELFT
Netherlands

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Open Research Data Pilot (1)

Data Management Plan

Report on how results data and publications will be made open access available under FAIR conditions

Pubblicazioni

Peer reviewed articles (19)

On the Regret of Model Predictive Control With Imperfect Inputs

Autori: Changrui Liu, Shengling Shi, Bart De Schutter
Pubblicato in: IEEE Control Systems Letters, Numero 9, 2025, Pagina/e 601-606, ISSN 2475-1456
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/lcsys.2025.3577083

Multi-agent reinforcement learning via distributed MPC as a function approximator

Autori: Mallick, Samuel; Airaldi, Filippo; Dabiri, Azita; De Schutter, Bart
Pubblicato in: Automatica, Numero 4, 2024, Pagina/e 111803, ISSN 0005-1098
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2024.111803

Distributed Model Predictive Control for Piecewise Affine Systems Based on Switching ADMM

Autori: Samuel Mallick, Azita Dabiri, Bart De Schutter
Pubblicato in: IEEE Transactions on Automatic Control, Numero 70, 2025, Pagina/e 3727-3741, ISSN 0018-9286
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2024.3512334

Reinforcement Learning With Model Predictive Control for Highway Ramp Metering

Autori: Filippo Airaldi, Bart De Schutter, Azita Dabiri
Pubblicato in: IEEE Transactions on Intelligent Transportation Systems, Numero 26, 2025, Pagina/e 5988-6004, ISSN 1524-9050
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2025.3549227

Approximate dynamic programming for constrained linear systems: A piecewise quadratic approximation approach

Autori: He, Kanghui; Shi, Shengling; Boom, Ton van den; De Schutter, Bart
Pubblicato in: Automatica, Numero 160, 2024, Pagina/e 111456, ISSN 0005-1098
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2023.111456

Bi-level model predictive control for metro networks: Integration of timetables, passenger flows, and train speed profiles

Autori: Xiaoyu Liu; Azita Dabiri; Jing Xun; Bart De Schutter
Pubblicato in: Transportation Research Part E: Logistics and Transportation Review, Numero 180, 2023, Pagina/e 103339, ISSN 1366-5545
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.tre.2023.103339

A combined probabilistic-fuzzy approach for dynamic modeling of traffic in smart cities: Handling imprecise and uncertain traffic data

Autori: A. Jamshidnejad and B. De Schutter
Pubblicato in: Computers and Electrical Engineering, 2024, Pagina/e 109552, ISSN 0045-7906
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.compeleceng.2024.109552

Deep Learning for Object Detection and Segmentation in Videos: Toward an Integration With Domain Knowledge

Autori: A. Ilioudi, A. Dabiri, B. J. Wolf and B. De Schutter
Pubblicato in: IEEE Access, Numero 10, 2022, Pagina/e 34562-34576, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2022.3162827

Distributed Model Predictive Control for Virtually Coupled Heterogeneous Trains: Comparison and Assessment

Autori: Xiaoyu Liu, Azita Dabiri, Yihui Wang, Jing Xun, Bart De Schutter
Pubblicato in: IEEE Transactions on Intelligent Transportation Systems, Numero 25, 2024, Pagina/e 20753-20766, ISSN 1524-9050
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2024.3458169

Adaptive parameterized model predictive control based on reinforcement learning: A synthesis framework

Autori: D. Sun, A. Jamshidnejad, and B. De Schutter
Pubblicato in: Engineering Applications of Artificial Intelligence, 2024, Pagina/e 109009, ISSN 0952-1976
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.engappai.2024.109009

Modeling and Efficient Passenger-Oriented Control for Urban Rail Transit Networks

Autori: Xiaoyu Liu; Azita Dabiri; Yihui Wang; Bart De Schutter
Pubblicato in: IEEE Transactions on Intelligent Transportation Systems, Numero 24, 2023, Pagina/e 3325-3338, ISSN 1524-9050
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2022.3228340

Learning-Based MPC for Fuel Efficient Control of Autonomous Vehicles With Discrete Gear Selection

Autori: Samuel Mallick, Gianpietro Battocletti, Qizhang Dong, Azita Dabiri, Bart De Schutter
Pubblicato in: IEEE Control Systems Letters, Numero 9, 2025, Pagina/e 1117-1122, ISSN 2475-1456
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/lcsys.2025.3575335

Finite-sample analysis of identification of switched linear systems with arbitrary or restricted switching

Autori: Shengling Shi; Othmane Mazhar; Bart De Schutter
Pubblicato in: IEEE Control Systems Letters, Numero 7, 2023, Pagina/e 121-126, ISSN 2475-1456
Editore: IEEE
DOI: 10.48550/arxiv.2203.09862

A Novel Framework Combining MPC and Deep Reinforcement Learning With Application to Freeway Traffic Control

Autori: Dingshan Sun; Anahita Jamshidnejad; Bart De Schutter
Pubblicato in: IEEE Transactions on Intelligent Transportation Systems, 2024, Pagina/e 6756-6769, ISSN 1524-9050
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2023.3342651

Grammatical-Evolution-based parameterized Model Predictive Control for urban traffic networks

Autori: Joost Jeschke; Dingshan Sun; Anahita Jamshidnejad; Bart De Schutter
Pubblicato in: Control Engineering Practice, Numero 132, 2023, Pagina/e 105431, ISSN 0967-0661
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.conengprac.2022.105431

Real-Time Train Scheduling With Uncertain Passenger Flows: A Scenario-Based Distributed Model Predictive Control Approach

Autori: Xiaoyu Liu; Azita Dabiri; Yihui Wang; Bart De Schutter
Pubblicato in: IEEE Transactions on Intelligent Transportation Systems, Numero 25, 2024, Pagina/e 4219-4232, ISSN 1524-9050
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2023.3329445

Reinforcement learning-based model predictive control for greenhouse climate control

Autori: Samuel Mallick, Filippo Airaldi, Azita Dabiri, Congcong Sun, Bart De Schutter
Pubblicato in: Smart Agricultural Technology, Numero 10, 2025, Pagina/e 100751, ISSN 2772-3755
Editore: Elsevier BV
DOI: 10.1016/j.atech.2024.100751

A Novel Bi-Level Temporally-Distributed Mpc Approach: An Application to Green Urban Mobility

Autori: Anahita Jamshidnejad; Dingshan Sun; Antonella Ferrara; Bart De Schutter
Pubblicato in: Transportation Research Part C: Emerging Technologies, Numero 156, 2023, Pagina/e 104334, ISSN 0968-090X
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.trc.2023.104334

Sensitivity analysis for piecewise-affine approximations of nonlinear programs with polytopic constraints

Autori: L. Gharavi; C. Liu; B. De Schutter; and S. Baldi
Pubblicato in: IEEE Control Systems Letters, 2024, Pagina/e 1271-1276, ISSN 2475-1456
Editore: IEEE
DOI: 10.1109/lcsys.2024.3408711

Conference proceedings (12)

Regret Analysis of Learning-Based Linear Quadratic Gaussian Control with Additive Exploration

Autori: Athrey, Archith; Mazhar, Othmane; Guo, Meichen; De Schutter, Bart; Shi, Shengling
Pubblicato in: Proceedings of the 2024 European Control Conference, 2024, Pagina/e 1795-1801
Editore: -
DOI: 10.23919/ecc64448.2024.10590739

Scenario-Based MPC for Real-Time Passenger-Centric Timetable Scheduling of Urban Rail Transit Networks

Autori: Liu, X. (author); Dabiri, A. (author); De Schutter, B.H.K. (author)
Pubblicato in: Proceedings of the 22nd IFAC World Congress / IFAC-PapersOnLine, 2023, Pagina/e 2347-2352
Editore: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.1205

Integrated reinforcement learning and optimization for railway timetable rescheduling

Autori: H. Zhang, X. Liu, D. Sun, A. Dabiri, and B. De Schutter
Pubblicato in: Proceedings of the 17th IFAC Symposium on Control in Transportation Systems (CTS 2024, 2024, Pagina/e 310-315
Editore: -
DOI: 10.1016/j.ifacol.2024.07.358

A Generalized Partitioning Strategy for Distributed Control

Autori: Alessandro Riccardi, Luca Laurenti, Bart De Schutter
Pubblicato in: 2024 IEEE 63rd Conference on Decision and Control (CDC), 2025, Pagina/e 6134-6141
Editore: IEEE
DOI: 10.1109/cdc56724.2024.10885848

Adaptive Parameterized Control for Coordinated traffic Management Using Reinforcement Learning

Autori: Sun, D. (author); Jamshidnejad, A. (author); De Schutter, B.H.K. (author)
Pubblicato in: Proceedings of the 22nd IFAC World Congress / IFAC-PapersOnLine, 2023, Pagina/e 5463-5468
Editore: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.198

Stability and Performance Analysis of Model Predictive Control of Uncertain Linear Systems

Autori: Changrui Liu, Shengling Shi, Bart De Schutter
Pubblicato in: 2024 IEEE 63rd Conference on Decision and Control (CDC), 2025, Pagina/e 7356-7362
Editore: IEEE
DOI: 10.1109/cdc56724.2024.10885798

Signal selection for local module identification in linear dynamic networks: A graphical approach

Autori: Shengling Shi, Xiaodong Cheng, Bart De Schutter, Paul M.J. Van den Hof
Pubblicato in: Proceedings of the 22nd IFAc World Congress / IFAC-PapersOnLine, 2023, Pagina/e 2407-2412
Editore: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.1215

Provably-Stable Stochastic MPC for a Class of Nonlinear Contractive Systems

Autori: Cordiano, F. (author); Fochesato, Marta (author); Huang, Linbin (author); De Schutter, B.H.K. (author)
Pubblicato in: Proceedings of the 22nd IFAC World Congress / IFAC-PapersOnLine, 2023, Pagina/e 11242-11248
Editore: IFAC
DOI: 10.1016/j.ifacol.2023.10.313

Efficient and Safe Learning-based Control of Piecewise Affine Systems Using Optimization-Free Safety Filters*

Autori: Kanghui He, Shengling Shi, Ton Van Den Boom, Bart De Schutter
Pubblicato in: 2024 IEEE 63rd Conference on Decision and Control (CDC), 2025, Pagina/e 5046-5053
Editore: IEEE
DOI: 10.1109/cdc56724.2024.10886328

A Behavioral Perspective on Models of Linear Dynamical Networks with Manifest Variables

Autori: S. Shi, Z. Sun, and B. De Schutter
Pubblicato in: Proceedings of the 2024 European Control Conference, 2024, Pagina/e 2927-2933
Editore: -
DOI: 10.23919/ecc64448.2024.10591178

Scenario reduction with guarantees for stochastic optimal control of linear systems

Autori: F. Cordiano; B. De Schutter
Pubblicato in: Proceedings of the 2024 European Control Conference, 2024, Pagina/e 3502-3508
Editore: -
DOI: 10.23919/ecc64448.2024.10590866

Learning safety in model-based Reinforcement Learning using MPC and Gaussian Processes

Autori: Airaldi, Filippo; De Schutter, Bart; Dabiri, Azita
Pubblicato in: Proceedings of the 22nd IFAC World Congress / Elsevier, 2023, Pagina/e 5759-5764
Editore: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.563

Book chapters (1)

A Benchmark for the Application of Distributed Control Techniques to the Electricity Network of the European Economic Area

Autori: Alessandro Riccardi, Luca Laurenti, Bart De Schutter
Pubblicato in: Advances in Industrial Control, Control Systems Benchmarks, 2025, Pagina/e 9-28
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-76312-0_2